BionoiNet: Ligand-binding site classification with off-the-shelf deep neural network

© The 2020 Author(s). Published by Oxford University Press. All rights reserved. Motivation: Fast and accurate classification of ligand-binding sites in proteins with respect to the class of binding molecules is invaluable not only to the automatic functional annotation of large datasets of protein structures but also to projects in protein evolution, protein engineering and drug development. Deep learning techniques, which have already been successfully applied to address challenging problems across various fields, are inherently suitable to classify ligand-binding pockets. Our goal is to demonstrate that off-the-shelf deep learning models can be employed with minimum development effort to recognize nucleotide-and heme-binding sites with a comparable accuracy to highly specialized, voxel-based methods. Results: We developed BionoiNet, a new deep learning-based framework implementing a popular ResNet model for image classification. BionoiNet first transforms the molecular structures of ligand-binding sites to 2D Voronoi diagrams, which are then used as the input to a pretrained convolutional neural network classifier. The ResNet model generalizes well to unseen data achieving the accuracy of 85.6% for nucleotide-and 91.3% for heme-binding pockets. BionoiNet also computes significance scores of pocket atoms, called BionoiScores, to provide meaningful insights into their interactions with ligand molecules. BionoiNet is a lightweight alternative to computationally expensive 3D architectures

Characterization of the enzyme kinetics of EMP and HMP pathway in Corynebacterium glutamicum: reference for modeling metabolic networks

The model of intracellular metabolic network based on enzyme kinetics parameters plays an important role in understanding the intracellular metabolic process of Corynebacterium glutamicum, and constructing such a model requires a large number of enzymological parameters. In this work, the genes encoding the relevant enzymes of the EMP and HMP metabolic pathways from Corynebacterium glutamicum ATCC 13032 were cloned, and engineered strains for protein expression with E.coli BL21 and P.pastoris X33 as hosts were constructed. The twelve enzymes (GLK, GPI, TPI, GAPDH, PGK, PMGA, ENO, ZWF, RPI, RPE, TKT, and TAL) were successfully expressed and purified by Ni2+ chelate affinity chromatography in their active forms. In addition, the kinetic parameters (Vmax, Km, and Kcat) of these enzymes were measured and calculated at the same pH and temperature. The kinetic parameters of enzymes associated with EMP and the HMP pathway were determined systematically and completely for the first time in C.glutamicum. These kinetic parameters enable the prediction of key enzymes and rate-limiting steps within the metabolic pathway, and support the construction of a metabolic network model for important metabolic pathways in C.glutamicum. Such analyses and models aid in understanding the metabolic behavior of the organism and can guide the efficient production of high-value chemicals using C.glutamicum as a host

Data from: Designing efficient hybrid strategies for information spreading in scale-free networks

Designing a spreading strategy is one of the critical issues strongly affecting spreading efficiency in complex networks. In this paper, to improve the efficiency of information spreading in scale-free networks, we propose four hybrid strategies by combing two basic strategies, i.e., (1) the LS (in which information is preferentially spread from the Large-degree vertices to the Small-degree ones) and (2) the SL (in which information is preferentially spread from the Small-degree vertices to the Large-degree ones). The objective in combining the two basic LS and SL strategies is to fully exploit the advantages of both strategies. To evaluate the spreading efficiency of the proposed four hybrid strategies, we first propose an information spreading model. Then, we introduce the details of the proposed hybrid strategies that are formulated by combining LS and SL. Third, we build a set of scale-free network structures by differently configuring the relevant parameters. In addition, finally, we conduct various Monte Carlo experiments to examine the spreading efficiency of the proposed hybrid strategies in different scale-free network structures. Experimental results indicate that the proposed hybrid strategies are effective and efficient for spreading information in scale-free networks

Relation of Mid-High-Latitude Eurasian ISO to Ural Blocking Frequency and Their Co-Effect on Extreme Hot Events during Boreal Summer

Based on NCEP reanalysis daily data during 1979–2018, the spatiotemporal evolution of the 10–30-day atmospheric intraseasonal oscillations (ISO) at mid-high-latitude Eurasia and its effect on the Ural blocking frequency are investigated. The co-effect of the blocking and ISO on extreme hot event frequency is also investigated. The ISO exhibits two modes of eastward and westward propagation. During the eastward (westward) propagating mode, the northwest–southeast tilted quadrupole (east–west dipole) quasi-barotropic geopotential height anomaly coupled with the air temperature anomaly at the troposphere propagates southeastward (westward). The phase composite shows that, during both modes, the mid-high-latitude low-frequency Rossby wave trains significantly affect the frequency of the European blocking during the propagating journey. The most frequent European blocking appears in phase 2 during both the eastward- and westward- propagating mode. Compared with the situation without the Ural blocking, the blocking activity results in the positive geopotential height anomalies throughout Europe and north of 60° N in the Ural Mountains and the negative geopotential height anomalies in the south of 60° N in the Ural Mountains and north of the Japan Sea. The occurrence of Ural blocking is conducive to the occurrence of extreme high-temperature events in Europe and the high latitudes of the Ural Mountains, and a reduced frequency of extreme high-temperature events in the mid-latitudes of the Ural Mountains and north of the Japan Sea. Therefore, the Ural blocking activities significantly regulate the effect of the two propagating ISO modes on the extreme hot events over the middle and high latitudes of Eurasia

Government Supports, Digital Capability, and Organizational Resilience Capacity during COVID-19: The Moderation Role of Organizational Unlearning

This paper provides an investigation into how different types of government supports can be used to enhance organizational resilience capacity during the COVID-19 pandemic. Based on resource orchestration theory, this study examines the effects of direct government support and indirect government support on organizational resilience capacity, the mediation role of digital capability, and the moderation effects of organizational unlearning. The empirical results from 205 Chinese firms show that direct government support and indirect government support have positive effects on organizational resilience capacity, which were mediated by digital capability. In addition, organizational unlearning positively and negatively moderates the positive relationship between direct government support, indirect government support and digital capability. Our theoretical discussion and empirical results contribute to the literature related to organizational resilience, digital capability, government support, and organizational unlearning

MicroRNAs: a critical regulator under mechanical force

Mechanical force is a kind of mechanical stimuli which actively participates in manipulating cellular activities in numerous types of cells. Progress in molecular and genetic research has uncovered various regulatory mechanisms underlying mechanical forceinduced changes in cellular activities, which include both transcriptional regulation and post-transcriptional regulation. MicroRNAs (miRNAs) are 20-25 nucleotide (nt) non-coding RNAs which serve as posttranscriptional regulators of multiple physiological processes. To date, considerable research effort has focused on the expressions and functions of miRNAs in a wide range of biological and pathological processes, including but not limited to development, proliferation, metabolism and osteogenic differentiation. In this review, major emphasis is placed on the biogenesis, expressions and functions of miRNAs in a mechanical environment